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Product

Agentic AI

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Resources

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Product

Agentic AI

Customers

Resources

Company

Product

Agentic AI

Customers

Resources

Company

Product

Agentic AI

Customers

Resources

Company

COGENT RESEARCH

Applied AI research for cybersecurity

Cogent Research works on the hardest problems in AI-driven security, with access to real enterprise data that no pure research setting can provide.

8,000+

Combined academic citations

2

Former Google DeepMind researchers

50%

Fortune 500 use team's prior work

Why cogent

A problem neither side can solve alone

Frontier AI talent clusters in big tech labs. Real security operations data lives inside enterprises. Nobody has had both. Cogent does.

AI Labs

World-class research talent and compute. No access to real enterprise security data.

Cogent

Frontier AI researchers with direct access to real operational data and outcome signals.

Security Vendors

Deep domain expertise and massive data. No frontier AI research capability.

THE TEAM

The researchers behind Cogent

Duc Hiep Chu

Head of Research

Former Google DeepMind. 4,000+ citations. Co-author of CodeMender, an AI agent that fixes code vulnerabilities before they reach downstream systems. Leader in formal verification.

Duc Hiep Chu

Head of Research

Former Google DeepMind. 4,000+ citations. Co-author of CodeMender, an AI agent that fixes code vulnerabilities before they reach downstream systems. Leader in formal verification.

Duc Hiep Chu

Head of Research

Former Google DeepMind. 4,000+ citations. Co-author of CodeMender, an AI agent that fixes code vulnerabilities before they reach downstream systems. Leader in formal verification.

RESEARCH PRIORITIES

What we're working on

Autonomous Security Agents

Controlled autonomy: agents act within guardrails, auditable steps, and continuous verification. Autonomy increases as trust compounds.

Formal Security Proofs

Mathematical certainty that an action is correct before an agent executes it. Fix the vulnerability, don't introduce new ones, preserve intended behavior.

Security Benchmarking

A standard evaluation framework for defensive AI. Designed to handle data contamination, automatic evaluation, and the cost-quality trade-offs existing benchmarks miss.

AI Reasoning for Security

Complex multi-step workflows execute in real time through graph traversal: mapping CVEs to assets, identifying patch policies, tracing ownership, checking remediation history, generating tickets.

Open-Source Models

Post-trained models for security tasks, released as open weights. Embedding models and agentic models for defensive workflows.

AI Threat Research

Agent skills and tool registries are becoming weaponized code marketplaces. We publish threat research on AI-specific attack vectors.

COGENT AI FELLOWSHIP

Do the work that matters most

A residency for researchers working in formal verification, reinforcement learning, or AI safety who want to apply it to real enterprise security data. The kind of domain-specific feedback loops that pure research settings cannot provide.